Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for restoring an image of a blurred barcode, the method comprising: capturing the image; restoring the image by selecting one Optical Transfer Function (OTF) in a database and performing deconvolution on the image; decoding the barcode in the restored image to return numbers represented by the barcode; and displaying the returned numbers, wherein, in the deconvolution of the barcode, a cutting threshold is determined, which adjusts to ambient lighting, to separate a white level from a black level in the barcode image in grayscale.
A method for restoring a blurred barcode image involves capturing the image and then restoring it by selecting an appropriate Optical Transfer Function (OTF) from a database. Deconvolution is performed using the selected OTF. The restored image is then decoded to extract the barcode's numerical representation, and these numbers are displayed. During deconvolution, a dynamic cutting threshold is determined, which adapts to the ambient lighting to differentiate between white and black levels within the grayscale barcode image, improving clarity and decoding accuracy.
2. The method of claim 1 , wherein the image comprises black and white dots representing pixels.
The barcode restoration method where a blurred barcode image is captured, restored using OTF selection and deconvolution, decoded, and displayed, using a dynamic cutting threshold that adjusts to ambient lighting, and where the image itself is composed of black and white dots that represent individual pixels.
3. The method of claim 1 , wherein pixels are spread due to incorrect focal length, and the spreading comprises a Point Spread Function (PSF), which is to be segmented for use.
The barcode restoration method where a blurred barcode image is captured, restored using OTF selection and deconvolution, decoded, and displayed, using a dynamic cutting threshold that adjusts to ambient lighting and where the image's blurring arises from an incorrect focal length causing pixels to spread. This pixel spreading is characterized by a Point Spread Function (PSF) that describes the blurring effect. This PSF is segmented from the image and used for the deconvolution process.
4. The method of claim 3 , wherein the deconvolution of the blurred image using the PSF or OTF estimates an image closest to the ideal for decoding the barcode, removing the blurring effect caused by the pixel spreading of the barcode image, and increasing a success rate of the method.
The barcode restoration method which includes capturing, OTF-based restoration and deconvolution, decoding, displaying restored numbers, a dynamic cutting threshold, and pixel spreading characterized by a Point Spread Function (PSF) to be segmented, and where deconvolution utilizes the PSF or Optical Transfer Function (OTF) to approximate an ideal, unblurred image. This process reduces blurring caused by pixel spreading, resulting in an improved success rate in decoding the barcode.
5. The method of claim 3 , further comprising a procedure for camera calibration which creates a database of PSF's, reflecting the impact of the blurring effect at a given point from a given distance, and the PSF's of this database are used in deconvolution that removes the blurring effect and restores the image with the barcode.
The barcode restoration method which includes capturing, OTF-based restoration and deconvolution, decoding, displaying restored numbers, a dynamic cutting threshold, pixel spreading characterized by a Point Spread Function (PSF) to be segmented, and deconvolution utilizing the PSF or Optical Transfer Function (OTF) to approximate an ideal, unblurred image and involves a camera calibration procedure. This calibration generates a database of PSFs, which reflects the blurring effect at various points and distances. These PSFs are then used in the deconvolution process to remove blur and restore the barcode image.
6. The method of claim 5 , further comprising extracting static PSF's for use in the deconvolution.
The barcode restoration method which includes capturing, OTF-based restoration and deconvolution, decoding, displaying restored numbers, a dynamic cutting threshold, pixel spreading characterized by a Point Spread Function (PSF) to be segmented, deconvolution utilizing the PSF or Optical Transfer Function (OTF) to approximate an ideal, unblurred image, and a camera calibration procedure to generate a PSF database, and also extracts static PSFs from the database for use in the deconvolution step.
7. The method of claim 5 , wherein the PSF data-base comprises data concerning a particular camera according to different models of cameras having different focal lengths.
The barcode restoration method which includes capturing, OTF-based restoration and deconvolution, decoding, displaying restored numbers, a dynamic cutting threshold, pixel spreading characterized by a Point Spread Function (PSF) to be segmented, deconvolution utilizing the PSF or Optical Transfer Function (OTF) to approximate an ideal, unblurred image, and a camera calibration procedure to generate a PSF database, where the PSF database contains camera-specific data. The data represents different camera models, accounting for variations in focal length.
8. The method of claim 3 , wherein a bank of PSF's are estimated.
The barcode restoration method which includes capturing, OTF-based restoration and deconvolution, decoding, displaying restored numbers, a dynamic cutting threshold, pixel spreading characterized by a Point Spread Function (PSF) to be segmented, and deconvolution utilizing the PSF or Optical Transfer Function (OTF) to approximate an ideal, unblurred image, and also involves estimating a bank of different PSFs (Point Spread Functions).
9. The method of claim 1 , further comprising: digitalizing the captured image by creating a mask of regions with probable positions of Point Spread Functions (PSF's); copying only values of PSF's, excluding a background image; cutting each one of PSF's present in the image to store them separately in an initial database, said database being analyzed to select the initial PSF's that best restore the image; verifying by decoding multiple barcodes applying blur PSF's from the database to restore the image; wherein the PSF's in which decoding is performed successfully are PSF's whose numbers are exactly equal to the numbers encoded by the selected barcodes.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, and includes a cutting threshold that adjusts to ambient lighting. Further, the method digitalizes the captured image by creating a mask of regions with probable Point Spread Function (PSF) locations. The method copies only the PSF values, excluding the background. Each PSF is cut and stored separately in an initial database. This database is analyzed to select the best initial PSFs for restoring the image. The method verifies by decoding multiple barcodes, applying blurring PSFs from the database to restore the image. PSFs that successfully decode to the correct barcode numbers are identified.
10. The method of claim 1 , wherein a size of a bar in the barcode is estimated considering a threshold based on the specific characteristics of dimensions of the barcode used in EAN-13.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, and includes a cutting threshold that adjusts to ambient lighting. Additionally, it estimates the size of a bar in the barcode based on a threshold derived from specific dimensional characteristics of the barcode (specifically, EAN-13 standard dimensions).
11. The method of claim 1 , wherein the image restoring enables the use of devices with no auto-focus.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, and includes a cutting threshold that adjusts to ambient lighting, where the image restoration process enables the use of cameras and devices lacking autofocus capabilities.
12. The method of claim 1 , further comprising performing real-time processing, and analyzing frames obtained in a preview mode.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, and includes a cutting threshold that adjusts to ambient lighting. The method performs real-time processing by analyzing frames obtained in a preview mode.
13. The method of claim 1 , wherein regions which do not belong to the barcode are excluded from processing.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, and includes a cutting threshold that adjusts to ambient lighting. It also excludes regions of the image that do not contain barcode elements, improving processing efficiency.
14. The method of claim 1 , wherein the barcode is sliced horizontally and reading is performed on each of these individual slices.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, and includes a cutting threshold that adjusts to ambient lighting. The method slices the barcode image horizontally and then performs barcode reading on each individual slice.
15. The method of claim 14 , wherein the number of slices is adjusted according to performance, so that slices of different positions and sizes are obtained, thus increasing the probability of success in decoding.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, includes a cutting threshold that adjusts to ambient lighting, and slices the barcode image horizontally and then performs barcode reading on each individual slice, where the number of slices is dynamically adjusted based on performance. Slices of varying positions and sizes are created to increase the probability of successful barcode decoding.
16. The method of claim 14 , wherein the slice to be decoded is divided into vertical regions and for each slice, a threshold is obtained in accordance with a pixel intensity.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, includes a cutting threshold that adjusts to ambient lighting, and slices the barcode image horizontally and then performs barcode reading on each individual slice, where each slice to be decoded is further divided into vertical regions. A threshold value, based on pixel intensity, is determined for each vertical region within the slice.
17. The method of claim 1 , wherein the decoding of barcodes is performed on images taken by cameras having low cost and fixed focus.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, and includes a cutting threshold that adjusts to ambient lighting, where the decoding of barcodes is performed on images captured by low-cost, fixed-focus cameras.
18. The method of claim 1 , further comprising mirroring the image of the barcode.
The barcode restoration method involves capturing a blurred barcode image, restoring the image, decoding, and displaying the decoded numbers, and includes a cutting threshold that adjusts to ambient lighting. The method also mirrors the barcode image during processing.
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October 21, 2014
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